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Expertise and hands-on experience in operating and maintaining analytical instruments including but not limited to GC, FTIR, UV-Vis, DSC, TGA, SEM, XPS, Raman, IC, 1H-NMR, and 19F-NMR. Ability to analyze data and draw deeper conclusions from analytical data to drive faster turnaround times.
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Advanced understanding of SEM using Google Ads, Bing Ads or other paid search engines. An understanding of the relationship between SEM and SEO, how they differ and can be used to improve overall search presence.
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Proficiency in materials characterization tools such as Inductively Coupled Plasma (ICP), X-ray Diffraction (XRD), Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM/EDS.
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Advanced knowledge of math, statistics, multivariate analysis, statistical tests Advanced Python coding skills Experience with one or more machine learning frameworks such as TensorFlow and/or PyTorch Understanding of numerical implementations Understanding of cloud computing Knowledge of data querying knowledge of EMG, EEG, ECG, IMU, CV algorithms Experience with C.
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The Core Data & Services for the Data organization within the DEET organization is in search of a Senior Data Engineer. Implement Ingestion of new batch and streaming data pipelines using Scala, Databricks, and Airflow.
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Deliver datasets from onboarding through mapping and automated DQ so they can be handed off to the Data Operations team for DQ maintenance and consumed by research teams and production. The Asset Management Quant Research Engineering team is looking for a Director of Data Engineering who wishes to take on the challenge of building a world-class data operation.
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Experience with software used for trading and financial data management such as Eagle, State Street Alpha, CRD, Aladdin, Factset, Bloomberg is a strong plus. Provide thought leadership on designing data capabilities for investment and asset management business functions across front-office, middle-office and back-office workflows.
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Proficiency in statistical programming languages (e.g., SAS, R) and clinical data management systems (e.g., Medidata Rave, Oracle Clinical) is essential. The Senior Vice President (SVP), Head of Data Analytics leads a multidisciplinary team responsible for biostatistics, statistical programming, and data management.
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We are seeking a rock star Senior Data Scientist to join our Risk Data team within the Ecosystem Fraud Team at Square. Create and maintain ETLs and data pipelines for continuous data integration and analysis.
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Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny) The Clinical Data Analyst partners cross functionally to identify risk to data integrity throughout the data flow to drive quality collection for non-EDC data sources (fluid & tissue labs, digital, imaging, wearables) in Dyne's clinical studies.
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You will work closely with a cross-functional team including media planners, paid media platform specialists (e.g., paid search, paid social, programmatic display), organic social and influencer marketing specialists, SEO, and digital strategists.
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No Search Firms:ALSAC does not accept unsolicited assistance from search firms for employment opportunities. All resumes submitted by search firms to any ALSAC employee or ALSAC representative via email, the internet or in any form and/or method without being contacted and approved by our Employee Experience team and without a valid written search agreement in place will result in no fee being paid if a referred candidate is hired by ALSAC.
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In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies. Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire.
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To Succeed in this Role, You Will: Plan, implement, manage, analyze, and optimize paid search engine marketing campaigns, such as Google Ads. Create and execute marketing campaigns, track their success, and perform necessary adjustments for continuous improvement.
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Data bases (SQL, NoSQL) and Data Platforms (Databricks, Snowflake) Strong skills with Database management, Data modeling and design DevOps and Security CI/CD, Serverless compute, OAuth, SSO, MFA etc.
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